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Design and develop high performing, scalable big data solutions in AWS and GCP to support advanced analytical use cases.
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Develop data pipelines for optimal extraction, transformation, and loading (ELT, ETL) from a wide variety of data sources using Big Data and Integration technologies.
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Design & develop feature, and code reviews to drive excellence in engineering and ensure high quality & maintainability.
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Implement effective solutions for cleansing & data quality, lineage.
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Support improvement of platform features for high productivity and availability.
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Bachelor’s degree in Information Systems, Computer Science, or related discipline. Master’s degree in Computer Science or related discipline is preferred.
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4 years of experience in developing big data solutions that support business analytics and data science teams.
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7 or more years of proficient experience developing data platforms, data warehouses, ETL/ELT pipelines and programming in SQL, Python, Java, Scala-Spark, Bash, and other scripting languages.
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Strong knowledge and hands on experience in Big Data technologies in Cloud such as AWS EMR, Apache Spark, Databricks, AWS Redshift, Snowflake, S3, GCP Big Query, Google Cloud Storage and Google Data Proc.
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Proven experience designing various batch & real-time streaming ingestion patterns with Sqoop, Kafka, Kinesis, GCP Pub/Sub.
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Proven leadership in cloud administration with emphasis on infrastructure automation (Terraform, Cloud Formation) and provisioning Lambda, SNS, EC2, Airflow, Elastic Cache, Redis, RESTful APIs in AWS.
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Knowledge of DevOps methodology and automation experience with Jenkins, Ansible, Chef, XL Release and XL Deploy.
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Prefer AWS/GCP Cloud certifications.
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Prefer AWS/GCP Data Engineering certifications.
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Prefer experience with automobile and/or manufacturing organizations.